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@@ -220,7 +220,6 @@ $$
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此即为公式(9.38)
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此即为公式(9.38)
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## 附录
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## 附录
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-
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参考公式
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参考公式
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$$
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$$
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\frac{\partial\boldsymbol x^TB\boldsymbol x}{\partial\boldsymbol x}=\left(B+B^T\right)\boldsymbol x
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\frac{\partial\boldsymbol x^TB\boldsymbol x}{\partial\boldsymbol x}=\left(B+B^T\right)\boldsymbol x
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@@ -231,10 +230,11 @@ $$
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$$
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$$
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\frac{\partial}{\partial x}\left(A^{-1}\right)=-A^{-1}\frac{\partial A}{\partial x}A^{-1}
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\frac{\partial}{\partial x}\left(A^{-1}\right)=-A^{-1}\frac{\partial A}{\partial x}A^{-1}
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$$
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$$
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-参考资料
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-[1] Meilă, Marina. "Comparing clusterings—an information based distance." Journal of multivariate analysis 98.5 (2007): 873-895.
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-[2] Halkidi, Maria, Yannis Batistakis, and Michalis Vazirgiannis. "On clustering validation techniques." Journal of intelligent information systems 17.2-3 (2001): 107-145.
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-[3] Petersen, K. B. & Pedersen, M. S. *The Matrix Cookbook*.
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-[4] Bishop, C. M. (2006). *Pattern Recognition and Machine Learning*. Springer.
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+
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+## 参考文献
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+[1] Meilă, Marina. "Comparing clusterings—an information based distance." Journal of multivariate analysis 98.5 (2007): 873-895.<br>
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+[2] Halkidi, Maria, Yannis Batistakis, and Michalis Vazirgiannis. "On clustering validation techniques." Journal of intelligent information systems 17.2-3 (2001): 107-145.<br>
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+[3] Petersen, K. B. & Pedersen, M. S. *The Matrix Cookbook*.<br>
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+[4] Bishop, C. M. (2006). *Pattern Recognition and Machine Learning*. Springer.<br>
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